JP2012238328A - Image processing device and image processing program - Google Patents

Abstract

PROBLEM TO BE SOLVED: To solve a problem in an image processing device that stability of an output image is low.SOLUTION: When calculating control points to designate a shape of a correction curve for image correction according to a feature of an input image, an image processing device divides a luminance histogram of the input image into a plurality of numerical ranges by grayscale, calculates number of pixels in each of the divided numerical regions and number of pixels in the input image, calculates a ratio or a magnitude relation of the number of pixels in each of the numerical regions to the number of pixels in the input image, and calculates the control points based on the calculated ratio or the calculated magnitude relation of each of the numerical regions.

Description

  The present invention relates to an image processing apparatus that calculates control points that specify the shape of a correction curve for correcting an image in accordance with the characteristics of an input image.

  2. Description of the Related Art Conventionally, image correction for correcting images such as moving images and still images is performed according to the characteristics of an input image, thereby outputting beautiful and easy-to-view images corresponding to various scenes. For example, in the case where an image taken with a digital camera or the like is used to correct an image such as a backlight image in which dark gradation is difficult to see, correction is performed to brighten the dark portion for each pixel of the image.

  In Non-Patent Document 1, as shown in FIGS. 17 and 18, image correction is performed so that the histogram after the image correction processing has a uniform distribution. Specifically, the histogram calculated from the input image is divided into a plurality of bins such as a dark part, an intermediate part, and a bright part according to the degree of brightness, and the scale is determined according to the ratio of the number of pixels in each bin to the total number of pixels. The image is corrected so that the histogram after image processing has a uniform distribution by enlarging the tone or reducing the gradation. FIGS. 17 and 18 are diagrams for explaining histogram equalization in image correction according to the related art.

  In Non-Patent Document 1, after equalizing the histogram, as shown in FIGS. 19 and 20, a correction curve used for image correction is calculated and image correction is performed. More specifically, image correction is performed using a correction curve calculated along with the ratio of the number of pixels in each bin to the total number of pixels. In other words, in Non-Patent Document 1, when the ratio of the number of dark pixels is large with respect to the entire image, as shown in FIG. 19, the correction amount of the dark part is the largest and the correction direction is corrected in a brighter direction. The On the other hand, in Non-Patent Document 1, when the ratio of the number of bright pixels is large with respect to the entire image, as shown in FIG. 20, the correction amount in the bright portion is the largest and the correction direction is also darkened Is done. 19 and 20 are diagrams for explaining image correction processing by histogram equalization according to the conventional technique.

R. C. Gonzalez, R.A. E. Woods, "Digital Image Processing", P91-P94

  However, the above-described conventional technique has a problem of cost. There is also a problem that the stability of the output image is low.

  Specifically, when correcting an image in which the gradation of a dark part such as a backlight image is difficult to see, it is necessary to control the correction amount for each pixel, and there is a problem that the cost increases because the processing increases. there were. Moreover, when the histogram after image correction is made uniform distribution as in Non-Patent Document 1, correction is performed without limiting the correction amount and the correction direction. As a result, the gradation becomes unnatural and there is a problem that the stability of the output image is low.

  Accordingly, the present invention has been made to solve the above-described problems of the prior art, and control for designating the shape of a correction curve capable of stably performing high-quality image correction without incurring costs. An object of the present invention is to provide an image processing apparatus that calculates points.

  In order to solve the above-described problems and achieve the object, an image processing apparatus disclosed in the present application is an image processing apparatus that calculates control points that specify the shape of a correction curve for correcting an image according to the characteristics of an input image. A dividing unit that divides the luminance histogram of the input image into a plurality of value ranges for each gradation; and calculates the number of pixels in each range divided by the dividing unit and the number of pixels of the input image, respectively. The ratio calculation means for calculating the ratio of the number of pixels in each range with respect to the number of pixels, and the ratio calculation means using relationship information indicating the relationship between the ratio of each range calculated by the ratio calculation means and the control point The control point between the bright part and the intermediate part and the control point between the intermediate part and the dark part are calculated from the ratio of each range calculated by the above, and the correction at the calculated control point is corrected to the output. The amount is a predetermined upper limit If the correction amount is larger, the correction amount is the upper limit value, and if the correction amount is smaller than the predetermined lower limit value, the correction amount is the lower limit value, and the control point between the bright part and the intermediate part and the intermediate part and the dark part are set. It is a requirement that control point calculation means for calculating control points is provided.

  According to the image processing device disclosed in the present application, it is possible to calculate a control point that specifies the shape of a correction curve whose correction amount is limited only from information obtained from a luminance histogram. Thus, it is possible to calculate a control point of a correction curve that can perform image correction with high quality.

FIG. 1 is a diagram illustrating an overview and features of the image processing apparatus according to the first embodiment. FIG. 2 is a block diagram illustrating the configuration of the image processing apparatus according to the first embodiment. FIG. 3 is a diagram illustrating an example of an equation for calculating the ordinates of the inflection points between the bright part and the intermediate part according to the first embodiment. FIG. 4 is a diagram illustrating an example of an expression for calculating the ordinate of the music point between the intermediate portion and the dark portion according to the first embodiment. FIG. 5 is a diagram illustrating an example of a Look-UpTable indicating the magnitude relationship of the brightness frequency. FIG. 6 is a diagram illustrating an example of equations used when calculating control points based on the Look-UpTable. FIG. 7 is a diagram illustrating an example of an equation for calculating the curvature correction amount according to the first embodiment. FIG. 8 is a diagram for explaining a case where the correction amount of the music point according to the first embodiment is limited. FIG. 9 is a diagram illustrating an example of an equation for calculating a correction curve according to the first embodiment. FIG. 10 is a diagram illustrating an example of a correction curve according to the first embodiment. FIG. 11 is a flowchart illustrating processing performed by the image processing apparatus according to the first embodiment. FIG. 12 is a diagram for explaining a process of calculating a music point with a limited change range according to the second embodiment. FIG. 13 is a diagram for explaining processing by the divided bin frequency calculation unit when the dark part and the bright part according to the third embodiment are further divided. FIG. 14 is a diagram for explaining processing by the control point calculation unit when the dark part and the bright part according to the third embodiment are further divided. FIG. 15 is a diagram for explaining processing for calculating the correction amount from the music point by linear interpolation. FIG. 16 is a diagram illustrating a computer that executes an image processing program. FIG. 17 is a diagram for explaining histogram equalization in image correction according to the related art. FIG. 18 is a diagram for explaining histogram equalization in image correction according to the related art. FIG. 19 is a diagram for explaining image correction processing by histogram equalization according to the related art. FIG. 20 is a diagram for explaining image correction processing by histogram equalization according to the related art.

  Embodiments of an image processing apparatus according to the present invention will be described below in detail with reference to the accompanying drawings. In the following, the outline and features of the image processing apparatus according to the first embodiment, the configuration of the image processing apparatus and the flow of processing will be described in order, and finally the effects of the present embodiment will be described. In the following embodiment, the control curve designating point of the correction curve will be described as an example of the control curve designating the shape of the correction curve. It is not limited.

[Outline and Features of Image Processing Device]
Next, the outline and features of the image processing apparatus according to the first embodiment will be described. FIG. 1 is a diagram illustrating an overview and features of the image processing apparatus according to the first embodiment.

  In general, in image processing such as a backlight image, the image quality of an image depends on how the dark part of the image is output. The image processing apparatus controls the shape of a correction curve for correcting an image according to the characteristics of an image such as a moving image or a still image input from another apparatus connected to the image processing apparatus. Calculate points.

  In such a configuration, the image processing apparatus outlines calculating control points that specify the shape of a correction curve for image correction according to the characteristics of the input image. The main feature is that it is possible to calculate a control point of a correction curve that can perform image correction stably and with high quality without applying.

  Explaining this main feature, when receiving an input image, the image processing apparatus calculates a luminance histogram of the image (see (1) in FIG. 1), and divides the luminance histogram of the image into a plurality of value ranges for each gradation. (See (2) in FIG. 1).

  As a specific example, when an image such as a moving image or a still image is received, the image processing apparatus reads the image, calculates a luminance component for each pixel, and calculates the appearance frequency of the calculated luminance component. The luminance histogram of the image is calculated from the above. Subsequently, the image processing apparatus displays the calculated luminance histogram in a plurality of dark portions (for example, 0 to 84 gradations), intermediate portions (for example, 85 to 168 gradations), and bright portions (for example, 169 to 255 gradations). Divide into range.

  Then, the image processing device calculates the number of pixels of each divided range and the number of pixels of the input image, and calculates the ratio or magnitude relationship of the number of pixels of each range with respect to the number of pixels of the input image. Then, control points for designating the shape of the correction curve for correcting the image are calculated based on the ratio or the magnitude relationship of each value range (see (3) in FIG. 1).

  More specifically, the image processing apparatus counts the number of pixels in each value range such as the divided dark part, intermediate part, and bright part. Then, the image processing apparatus calculates a ratio or a magnitude relationship of the counted number of pixels in each range with respect to the total number of pixels. Subsequently, the image processing apparatus calculates a curvature point (control point) that is a change point of a correction curve used for image correction, using the calculated ratio or magnitude relationship of each value range such as a dark part, an intermediate part, and a bright part. To do. Thereafter, the image processing apparatus calculates a final music point in which the calculated music point is further limited to a correction amount within a predetermined range.

  Subsequently, the image processing apparatus calculates a correction curve based on the calculated control point, and corrects the input image based on the calculated correction curve (see (4) in FIG. 1). Specifically, in the above example, the image processing apparatus calculates a correction curve based on the inflection point where the calculated correction amount is limited. Then, the image processing apparatus corrects the input image by obtaining an output value from the input value based on the calculated correction curve, and outputs a corrected image.

  As described above, the image processing apparatus according to the first embodiment uses the ratio of the number of pixels in each range divided only from the luminance histogram information of the input image such as a moving image or a still image, to adjust the gradation. As a result of calculating the curve point of the correction curve to be corrected, it is possible to calculate the control point of the correction curve that can stably perform high-quality image correction without cost.

[Configuration of image processing apparatus]
Next, the configuration of the image processing apparatus according to the first embodiment will be described with reference to FIG. FIG. 2 is a block diagram illustrating the configuration of the image processing apparatus according to the first embodiment. As illustrated in FIG. 2, the image processing apparatus 10 includes an I / F unit 11, a storage unit 20, and a control unit 30, and controls a correction curve used for image correction according to an input image that is input. Calculate points.

  The I / F unit 11 receives an input image such as a moving image or a still image input from another device connected to the image processing device 10 and inputs the input image to a luminance histogram calculation unit 31 described later. Note that moving images and still images may be input from a storage medium such as a CD-R as well as other connected devices.

  The storage unit 20 stores data necessary for various types of processing by the control unit 30 and various types of processing results by the control unit 30, and particularly those closely related to the present invention include an input image storage unit 21 and a correction curve. And a storage unit 22.

  The input image storage unit 21 stores input images such as moving images and still images input to the image processing apparatus 10. The correction curve storage unit 22 stores a correction curve (see FIG. 10) used for image correction calculated by a correction curve calculation unit 34 described later. FIG. 10 is a diagram illustrating an example of a correction curve according to the first embodiment.

  The control unit 30 has an internal memory for storing a control program, a program assuming various processing procedures, and necessary data, and particularly as closely related to the present invention, a luminance histogram calculation unit 31; A divided bin frequency calculation unit 32, a control point calculation unit 33, a correction curve calculation unit 34, and an image correction unit 35 are provided, and various processes are executed by these units.

  The luminance histogram calculation unit 31 receives an input image and calculates a luminance histogram of the image. Specifically, when receiving an input image, the luminance histogram calculation unit 31 stores the image or the reduced image in the input image storage unit 21. Then, the luminance histogram calculation unit 31 reads an image or a reduced image stored in the input image storage unit 21 and calculates the Y component (luminance component) for each pixel from the RGB components as “Y = 0.299 × R + 0.587 × G + 0. ..114 × B ”or the like. Subsequently, the luminance histogram calculation unit 31 counts the frequency of the calculated Y component, and calculates a luminance histogram of the image or reduced image based on the Y value of each pixel.

  The divided bin frequency calculation unit 32 divides the luminance histogram of the input image into a plurality of value ranges for each gradation, calculates the number of pixels of each divided value range and the number of pixels of the input image, respectively, The ratio or the magnitude relationship of the number of pixels in each range with respect to the number is calculated. To give a specific example in the above example, the divided bin frequency calculation unit 32 uses the luminance histogram calculated by the luminance histogram calculation unit 31 as “0 to 84 gradation: dark part” and “85 to 168 gradation: intermediate. Part "," 169-255 gradation: bright part ", etc., and is divided into a plurality of value ranges. Then, the divided bin frequency calculation unit 32 counts the number of pixels in each of the divided dark area, intermediate area, and bright area (for example, dark area “5”, intermediate area “1”, bright area “4”, etc.). Then, the ratio (for example, dark portion “5/10”, intermediate portion “1/10”, bright portion “4/10”, etc.) with respect to the total number of pixels “10” is calculated.

  The control point calculation unit 33 calculates a control point that designates the shape of a correction curve for image correction based on the calculated ratio or magnitude relationship of each value range. To give a specific example in the above example, the control point calculation unit 33 uses the ratios of the respective ranges of the dark part, the intermediate part, and the bright part calculated by the divided bin frequency calculation part 32 as shown in FIG. Based on this formula, the ordinate “255 × (1−4 / (2 × 10)) = 204” of the music point between the bright part and the intermediate part is calculated. Here, the abscissa of the inflection point between the bright part and the intermediate part is “Th2 = 168”, and the weight W1 is “W1 = 2”. And the control point calculation part 33 uses the inflection point (168,204) between the calculated bright part and the intermediate part, and based on an equation as shown in FIG. 4, between the intermediate part and the dark part. The ordinate of the music point “204-255 × (1 / (0.5 × 10)) = 153” is calculated. Here, the abscissa of the inflection point between the intermediate part and the dark part is “Th1 = 84”, and the weight W2 is “W2 = 0.5”.

  That is, the control point calculation unit 33 calculates the light point (168, 204) between the bright part and the intermediate part which are bright parts in the image, and uses the calculated bright part music point as the dark part. Since the inflection point (84, 153) between the dark part and the dark part is calculated, it is possible to correct the dark part reflecting the correction value of the bright part in the correction of the overall dark image such as the backlight image. 3 is a diagram illustrating an example of an expression for calculating the ordinates of the inflection points between the bright part and the intermediate part according to the first embodiment, and FIG. 4 illustrates the intermediate part and the dark part according to the first embodiment. It is a figure which shows the example of the type | formula for calculating the ordinate of the music point.

  In addition, the calculation of the control point that specifies the shape of the correction curve is one of the control point (curved point) calculation using the magnitude relationship between the bright part, the intermediate part, and the dark part. Although the case of calculating has been described, the control point can also be calculated based on the brightness frequency stored in advance. More specifically, the control point calculation unit 33 calculates control points based on an LUT (Look-Up Table) shown in FIG. FIG. 5 is a diagram illustrating an example of a Look-UpTable indicating the magnitude relationship between the brightness degrees.

  The calculation of the control points using the LUT is performed using, for example, the equations shown in FIGS. 6A and 6B. Further, in the control point calculation formula using the LUT, similar to the example of the curve point calculation formula shown in FIGS. The control points of the intermediate part and the dark part are calculated using the control point calculation results of the intermediate part and the intermediate part. FIG. 6 is a diagram illustrating an example of equations used when calculating control points based on the Look-UpTable.

  Subsequently, the control point calculation unit 33 further limits the calculated music points within a predetermined range. To give a specific example in the above example, the control point calculation unit 33 converts the calculated music points (168, 204) and (84, 153) into the correction amount “ 204-168 = 36 "and" 153-84 = 69 "are calculated. Further, the control point calculation unit 33 calculates the correction amount of the music point based on the restriction as shown in FIG.

  That is, the control point calculation unit 33 sets the correction amount to Th5 and the change range “36” or “69” to Th5 and Th6 when the change range “36” or “69” is equal to or less than Th5 for the calculated music point. If the correction amount is between “36” or “69”, and the change range “36” or “69” is equal to or greater than Th6, the correction amount is Th6, and the final inflection point (84, 84 + Th5), (84,153) or (84,84 + Th6) and (168,168 + Th5), (168,204) or (168,168 + Th6) are calculated. As a result, the control point calculation unit 33 calculates the curved point for correcting the image in the bright direction adjusted to “Th5” at the minimum, and “Th6” at the maximum, so that it looks like a backlight image. Correction curve control points for stable and high-quality image correction without correcting dark areas more than necessary or correcting bright areas more than necessary even when correcting dark images Can be calculated. FIG. 7 is a diagram illustrating an example of an equation for calculating the correction amount of the music point according to the first embodiment, and FIG. 8 illustrates a case where the correction amount of the music point according to the first embodiment is limited. It is a figure for doing.

  Thereafter, the correction curve calculation unit 34 calculates a correction curve based on the music point calculated by the control point calculation unit 33. Specifically, in the above example, the correction curve calculation unit 34, as shown in FIG. 10, is a curved point calculated from a bright part and an intermediate part whose correction amount is limited by the control point calculation unit 33. Based on 1 (x1, y1) and the inflection point 2 (x2, y2) calculated from the intermediate portion and the dark portion, a correction curve indicated by a straight line based on an equation as shown in FIG. (A) is calculated.

  Further, as shown in FIG. 10, the correction curve calculation unit 34 includes a curved point 1 (x1, y1) calculated from the bright part and the intermediate part, the correction amount of which is limited by the control point calculation part 33, and the intermediate part. The correction curve (B) indicated by the curve may be calculated based on the equation shown in FIG. 9B based on the music point 2 (x2, y2) calculated from the dark portion and the dark portion. . FIG. 9 is a diagram illustrating an example of an equation for calculating the correction curve according to the first embodiment, and FIG. 10 is a diagram illustrating an example of the correction curve according to the first embodiment.

  The image correction unit 35 corrects the input image based on the correction curve calculated by the correction curve calculation unit 34. To give a specific example in the above example, the image correction unit 35 determines whether the received image or the reduced image is based on the correction curve (A) or the correction curve (B) calculated by the correction curve calculation unit 34. Make corrections. In image correction, a curve may be applied to the Y component of the image and then inverse conversion to the RGB component, or a curve may be applied directly to the RGB component.

[Processing by Image Processing Apparatus According to First Embodiment]
Next, processing performed by the image processing apparatus 10 according to the first embodiment will be described with reference to FIG. FIG. 11 is a flowchart illustrating processing performed by the image processing apparatus 10 according to the first embodiment.

  As shown in FIG. 11, when an image is input to the image processing apparatus 10 (Yes in step S101), the image processing apparatus 10 reads the image or the reduced image and calculates a Y component for each pixel from the RGB components. The frequency of the calculated Y component is counted, and a luminance histogram of the image or reduced image is calculated based on the Y value of each pixel (step S102).

  Then, the image processing apparatus 10 divides the calculated luminance histogram into a plurality of value ranges for each gradation such as a dark portion, an intermediate portion, and a bright portion (step S103), and each of the divided dark portion, intermediate portion, and bright portion is divided. The number of pixels in the range is counted, and a ratio or a magnitude relationship with respect to the total number of pixels in each range is calculated (step S104).

  Subsequently, the image processing apparatus 10 uses the calculated ratios or magnitude relationships of the respective ranges of the dark part, the intermediate part, and the bright part to convert the inflection points of the bright part, the intermediate part, the intermediate part, and the dark part into the bright part. While calculating each while reflecting a correction value, the music point which limited the change range of the calculated music point is calculated (step S105).

  Thereafter, the image processing apparatus 10 calculates a correction curve based on the calculated curvature point (step S106), and corrects the input image or the reduced image based on the calculated correction curve (step S107). . Specifically, the correction curve is generated by a “polyline” that connects the control points with a straight line, but a curve such as “spline” may be used.

[Effects of Example 1]
As described above, the image processing apparatus 10 calculates the control point for designating the shape of the correction curve with the limited change range used for correcting the image from the information of the luminance histogram of the input image to be input. Therefore, it is possible to calculate a control point of a correction curve that can stably perform high-quality image correction without incurring costs.

  For example, the image processing apparatus 10 calculates a luminance histogram of the input image and divides the luminance histogram into a plurality of value ranges such as a dark portion, an intermediate portion, and a bright portion for each gradation. Then, the image processing apparatus 10 calculates a ratio or a magnitude relationship with respect to the total number of pixels in each divided value range. Subsequently, the image processing apparatus 10 calculates the control points (curvature points) between the bright part and the intermediate part and the intermediate part and the dark part while limiting the correction amount, using the calculated ratio or magnitude relationship of each range. To do. Thereafter, the image processing apparatus 10 calculates a correction curve using the calculated control points, and corrects the input image input based on the calculated correction curve. That is, the image processing apparatus 10 can calculate a control point with a limited correction amount from only information obtained from the luminance histogram, and as a result, can stably perform high-quality image correction without incurring costs. It is possible to calculate a control point of a correction curve that can be obtained.

  By the way, in the first embodiment, a case has been described in which the inflection point with a limited change range is calculated using a predetermined fixed value such as “Th5” or “Th6”, but the present invention is not limited to this. Alternatively, the music point correction amount curve may be stored in advance in a predetermined storage unit, and the music point may be calculated using the music point correction amount curve.

[Process of calculating a music point with a limited change range according to the second embodiment]
Therefore, in the following second embodiment, a process for calculating the inflection point with a limited change range by the image processing apparatus 10 according to the second embodiment will be described with reference to FIG. FIG. 12 is a diagram for explaining a process of calculating a music point with a limited change range according to the second embodiment. The processing other than the process of calculating the inflection point with the limited change range is the same as that of the first embodiment, and therefore the description thereof is omitted. Here, the inflection point with the limited change range is calculated. Processing to be performed will be described.

  The difference from the first embodiment is that a curvature correction amount curve indicating a correction amount with a limited change range is stored in association with the correction amount. Specifically, as shown in FIG. 12, using a curvature correction curve for which a predetermined fixed value is not defined, the range of change of the correction amount calculated based on the equation shown in FIG. A typical music point is calculated.

[Effects of Example 2]
In this way, the image processing apparatus 10 holds the curve point correction amount curve indicating the correction amount in which the change range is limited in association with the curvature point correction amount, and the final music piece is based on the calculated correction amount. Since the points are calculated, it is possible to calculate the correction amount of the curvature point with higher accuracy and to calculate the curvature point of the correction curve for performing image correction with high quality.

  By the way, in the first embodiment, the case where the brightness histogram is calculated by dividing the luminance histogram into the dark part, the intermediate part, and the bright part for each gradation has been described, but the present invention is not limited to this, and the dark part and the dark part are calculated. It is also possible to calculate the inflection point by further dividing the bright part.

[Processing by Divided Bin Frequency Calculation Unit According to Third Embodiment]
Therefore, in the following third embodiment, processing performed by the image processing apparatus 10 according to the third embodiment will be described with reference to FIGS. 13 and 14. FIG. 13 is a diagram for explaining processing by the divided bin frequency calculation unit 32 when the dark part and the bright part according to the third embodiment are further divided, and FIG. 14 is a diagram illustrating the dark part and the bright part according to the third embodiment. It is a figure for demonstrating the process by the control point calculation part 33 when these are further divided | segmented.

  Also, the variable “i” used in FIG. 13 indicates the gradation of 0 to 255, and “Hist (i)” indicates the gradation value of each pixel of the luminance histogram to be processed. Further, the predetermined values “Th1 to Th4” used in FIG. 13 are values such as “Th1 = 84”, “Th2 = 168”, “Th3 = 42”, and “Th4 = 212”, for example. Since the configuration and some functions of the image processing apparatus 10 according to the third embodiment are the same as those in the first embodiment, the description thereof is omitted, and here, the divided bin frequency different from that in the first embodiment. Processing by the calculation unit 32 and the control point calculation unit 33 will be described.

  As shown in FIG. 13, when the luminance histogram of the input image is calculated by the luminance histogram calculation unit 31 (Yes in step S201), the divided bin frequency calculation unit 32 sets the variable i to “i = 0” (step S202). ), The gradation value “Hist (i)” of the pixel of the luminance histogram is compared with the predetermined value “Th1” (step S203).

  Then, when the gradation value “Hist (i) = 30” of the pixel of the luminance histogram is smaller than the predetermined value “Th1 = 84” (Yes at Step S203), the divided bin frequency calculation unit 32 sets the pixel to the dark frequency. (Step S204).

  Subsequently, when the gradation value “Hist (i) = 30” of the pixel of the luminance histogram is smaller than the predetermined value “Th3 = 42” (Yes at Step S205), the divided bin frequency calculation unit 32 sets the pixel as a dark part. Counting as frequency A (step S206), and when the gradation value “Hist (i) = 50” of the pixel of the luminance histogram is equal to or greater than the predetermined value “Th3 = 42” (No at step S205), the pixel is darkened Count as frequency B (step S207).

  Thereafter, the divided bin frequency calculation unit 32 sets the variable i to “i = i + 1” (step S208), and ends the process when the variable i is “255” or more (No in step S209). If the variable i is smaller than “255” (Yes at Step S209), the divided bin frequency calculation unit 32 performs the process at Step S203.

  Further, the divided bin frequency calculation unit 32 determines that the luminance value “Hist (i) = 90” of the pixel of the luminance histogram is equal to or larger than the predetermined value “Th1 = 84” in Step S203 (No in Step S203). The gradation value “Hist (i)” of the pixel of the histogram is compared with the predetermined value “Th2” (step S210).

  Then, when the gradation value “Hist (i) = 100” of the pixel of the luminance histogram is smaller than the predetermined value “Th2 = 168” (Yes at Step S210), the divided bin frequency calculation unit 32 sets the pixel to the intermediate portion. Counting as a frequency (step S211), the process of step S208 is performed.

  In addition, when the gradation value “Hist (i) = 200” of the pixel of the luminance histogram is equal to or larger than the predetermined value “Th2 = 168” in Step S210 (No in Step S210), the divided bin frequency calculation unit 32 The pixel is counted as the bright part frequency (step S212).

  Then, when the gradation value “Hist (i) = 200” of the pixel of the luminance histogram is smaller than the predetermined value “Th4 = 212” (Yes in step S213), the divided bin frequency calculation unit 32 sets the pixel as a bright part. Counting as frequency A (step S214), when the gradation value “Hist (i) = 230” of the pixel of the luminance histogram is equal to or greater than the predetermined value “Th4 = 212” (No at step S213), the pixel is bright Counting as the frequency B (step S215), the process of step S208 is performed.

  The divided bin frequency calculation unit 32, when counting the gradation values of all the pixels, performs the same processing as in the first embodiment, and calculates the ratio of the number of pixels in each value range to the number of pixels of the input image. That is, the divided bin frequency calculation unit 32 calculates the ratio of the number of pixels of the dark part A, the dark part B, the intermediate part, the bright part A, and the bright part B to the number of pixels of the input image.

[Processing by Control Point Calculation Unit According to Embodiment 3]
Next, processing by the control point calculation unit 33 according to the third embodiment will be described. As shown in FIG. 14, when the ratio of the number of pixels in each range is calculated by the divided bin frequency calculation unit 32 (Yes in step S301), the control point calculation unit 33 performs the same processing as in the first embodiment, A music point with a limited change range between the bright part and the intermediate part is calculated (steps S302 and S303).

  Then, the control point calculation unit 33 calculates a music point in which the change range between the intermediate part and the dark part is limited (steps S304 and S305). Subsequently, the control point calculation unit 33 calculates a music point with a limited change range between the dark part A and the dark part B based on the music point with a limited change range between the intermediate part and the dark part (step S306, Step S307). Thereafter, the control point calculation unit 33 calculates the inflection point in which the change range between the bright part A and the bright part B is restricted based on the inflection point in which the change range between the bright part and the intermediate part is restricted (step). S308, step S309).

[Effects of Example 3]
As described above, the image processing apparatus 10 further divides the dark portion and the bright portion based on the gradation value of the input pixel, and calculates the ratio of the divided value ranges to the number of pixels of the input image. Since the inflection point with a limited change range is calculated based on the calculated ratio of each range, it is possible to calculate the inflection point of the correction curve for performing image correction with higher quality. .

  Although the embodiments of the present invention have been described so far, the present invention may be implemented in various different forms other than the embodiments described above. Accordingly, different embodiments will be described by dividing (1) calculating the correction amount by linear interpolation, (2) system configuration, and (3) program.

(1) Calculation of correction amount by linear interpolation In the above first to third embodiments, a case has been described in which a correction curve is calculated based on the calculated curvature point and the input image is corrected based on the calculated correction curve. The present invention is not limited to this, and the correction amount can also be calculated by linearly interpolating the calculated music points.

For example, as illustrated in FIG. 15, the image processing apparatus 10 calculates the origin (0, 0) and the curvature point 1 when the curvature point 1 (x1, y1) and the curvature point 2 (x2, y2) are calculated. a point located between the (x0, y0) and a point located between the inflection point 1 and Kyokuten 2 _(x n, _{y n)} by such as a linear interpolation of _{"x n} and each input value" x0 " , The output values “y0” and “y _n ” are calculated, and image correction processing is performed using the output values as the correction amount of the input image. That is, when the curvature point of the correction curve for correcting the image is calculated, the image processing apparatus 10 performs the image correction without calculating the correction curve for correcting the image. Can be implemented. FIG. 15 is a diagram for explaining processing for calculating a correction amount from a music point by linear interpolation.

(2) System Configuration In addition, information including the processing procedure, control procedure, specific name, various data and parameters shown in the document and drawings (for example, stored in the correction curve storage unit 22 shown in FIG. 2). Information such as a correction curve) can be arbitrarily changed unless otherwise specified.

  Further, each component of each illustrated apparatus is functionally conceptual, and does not necessarily need to be physically configured as illustrated. That is, the specific form of distribution / integration of each device is not limited to the illustrated one. For example, the luminance histogram calculation unit 31 receives an input image and stores it in the input image storage unit 21, and a luminance histogram. All or a part of the luminance histogram calculation unit to be calculated can be configured to be functionally or physically distributed / integrated in arbitrary units according to various loads or usage conditions. Furthermore, all or a part of each processing function performed in each device may be realized by a CPU and a program that is analyzed and executed by the CPU, or may be realized as hardware by wired logic.

(3) Program The image processing apparatus described in the present embodiment can be realized by executing a prepared program on a computer such as a personal computer or a workstation. In the following, an example of a computer that executes an image processing program having the same function as that of the image processing apparatus described in the above embodiment will be described with reference to FIG. FIG. 16 is a diagram illustrating a computer that executes an image processing program.

  As shown in FIG. 16, a computer 110 as an image processing apparatus is configured by connecting an HDD 130, a CPU 140, a ROM 150, and a RAM 160 through a bus 180 or the like.

  The ROM 150 has an image processing program that exhibits the same function as that of the image processing apparatus 10 shown in the first embodiment, that is, a division program 150a, a ratio / size relationship calculation program 150b, and a control as shown in FIG. A point calculation program 150c is stored in advance. Note that these programs 150a to 150c may be appropriately integrated or distributed in the same manner as each component of the image processing apparatus 10 shown in FIG.

  Then, the CPU 140 reads out these programs 150a to 150c from the ROM 150 and executes them, so that as shown in FIG. 16, the programs 150a to 150c have a division process 140a, a ratio / magnitude relationship calculation process 140b, and a control. It functions as the point calculation process 140c. The processes 140a to 140c correspond to the luminance histogram calculation unit 31, the divided bin frequency calculation unit 32, and the control point calculation unit 33 shown in FIG.

  Then, the CPU 140 executes an image processing program based on the data recorded in the RAM 160.

  The above-described programs 150a to 150c are not necessarily stored in the ROM 150 from the beginning. For example, a flexible disk (FD), a CD-ROM, a DVD disk, a magneto-optical disk inserted into the computer 110, It is connected to the computer 110 via a “portable physical medium” such as an IC card, or a “fixed physical medium” such as an HDD provided inside or outside the computer 110, and further via a public line, the Internet, a LAN, a WAN, etc. Each program may be stored in “another computer (or server)” or the like, and the computer 110 may read and execute each program from now on.

DESCRIPTION OF SYMBOLS 10 Image processing apparatus 11 I / F part 20 Storage part 21 Input image storage part 22 Correction curve storage part 30 Control part 31 Luminance histogram calculation part 32 Divided bin frequency calculation part 33 Control point calculation part 34 Correction curve calculation part 35 Image correction part

Claims (2)

An image processing device that calculates a control point for designating a shape of a correction curve for correcting an image according to a feature of an input image,
Dividing means for dividing the luminance histogram of the input image into a plurality of value ranges of dark part, intermediate part and bright part for each gradation, and further dividing the dark part and the bright part into a plurality of value ranges;
A ratio calculating unit that calculates the number of pixels in each range and the number of pixels in the input image divided by the dividing unit, and calculates the ratio of the number of pixels in each range with respect to the number of pixels in the input image;
Using the relationship information indicating the relationship between the ratio of the number of pixels in each range and the control point, from the ratio of each range calculated by the ratio calculation means, the control point between the bright part and the intermediate part, and When the control point between the intermediate part and the dark part is calculated and the correction amount for correcting the input at the calculated control point to the output is larger than the predetermined upper limit value, the correction amount is set to the upper limit value, and the correction amount is set to the predetermined amount. If it is smaller than the lower limit value, the control point calculation means for calculating the control point between the bright part and the intermediate part and the control point between the intermediate part and the dark part with the correction amount as the lower limit value;
An image processing apparatus comprising: An image processing program to be executed by a computer as an image processing apparatus that calculates a control point for designating a shape of a correction curve for correcting an image according to a feature of an input image,
A division procedure for dividing the luminance histogram of the input image into a plurality of value areas of a dark part, an intermediate part, and a light part for each gradation, and further dividing the dark part and the light part into a plurality of value areas;
A ratio calculation procedure for calculating the number of pixels in each range and the number of pixels in the input image, respectively, and calculating the ratio of the number of pixels in each range with respect to the number of pixels in the input image;
Using the relationship information indicating the relationship between the ratio of the number of pixels in each range and the control point, from the ratio of each range calculated by the ratio calculation procedure, the control point between the bright part and the intermediate part, and When the control point between the intermediate part and the dark part is calculated and the correction amount for correcting the input at the calculated control point to the output is larger than the predetermined upper limit value, the correction amount is set to the upper limit value, and the correction amount is set to the predetermined amount. If it is smaller than the lower limit value, the control point calculation procedure for calculating the control point between the bright part and the intermediate part and the control point between the intermediate part and the dark part with the correction amount as the lower limit value;
An image processing program for causing a computer to execute.

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